Coevolution between microbes and their viruses influences the trajectories of these communities through gene transfer and predation. When these communities are a part of the human microbiome, these interactions can also have significant impacts on the health of the human host. The CRISPR adaptive immune system is one of the ways in which microbes defend against viral infection, and it also holds a record of acquired immunity, allowing us to read a history of microbe-viral interactions. In this work, we examine the emergence, impact, and applications of diverse CRISPR immune alleles in microbial populations. Using a mathematical model of CRISPR-mediated host-virus coevolution to simulate microbial populations, we observe the emergence of multiple coexisting CRISPR alleles in a single population, which we call distributed immunity. We find that distributed immunity is most likely to occur in communities with more potential spacers and relatively low viral mutation rates, and that it is linked to increased stability for the host population, while the viral population is driven to lower densities or even to extinction. To see if this phenomenon is also present in natural microbial populations, we examined CRISPR diversity in two human-associated communities: the vaginal microbiomes of pregnant women and the lung microbiomes of cystic fibrosis patients. To investigate the vaginal microbiome, we developed a network-based methodology to identify and extract CRISPR spacers from all species present in samples taken from pregnant women at high and low risk of preterm birth. This approach yielded over 20 different CRISPR types, with spacer content varying among individuals. Coexisting alleles linked to shifts in the abundance of the matched element were detected in one Lactobacillus species in one of the samples, demonstrating the potential of our approach. In the cystic fibrosis lung microbiome, we used this method to identify CRISPRs in four patients infected with the major cystic fibrosis pathogen Pseudomonas aeruginosa. Spacer content was completely different between patients, but no variation was detected within a patient. Finally, we examined spacer diversity in a large global dataset of P. aeruginosa and used the thousands of spacers identified as a tracking tool to monitor dynamics of viral populations. This approach, which we refer to as prototyping, revealed a panmictic P. aeruginosa phage population and holds promise as a tool for tracking mobile elements and personalizing phage therapy treatments.